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Predictive inference of dual generalized order statistics from the inverse Weibull distribution

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  • Amany E. Aly

    (Helwan University)

Abstract

In this paper, some predictive results of dual generalized order statistics (DGOSs) from the inverse Weibull distribution are obtained. For this goal, different predictive and reconstructive pivotal quantities are proposed. Moreover, several predictive and reconstructive intervals concerning DGOSs based on the inverse Weibull distribution are constructed. Furthermore, the maximum likelihood predictor as well as the predictive maximum likelihood estimates based on DGOSs are studied. Finally, simulation studies are carried out to assess the efficiency of the obtained results.

Suggested Citation

  • Amany E. Aly, 2023. "Predictive inference of dual generalized order statistics from the inverse Weibull distribution," Statistical Papers, Springer, vol. 64(1), pages 139-160, February.
    • Handle: RePEc:spr:stpapr:v:64:y:2023:i:1:d:10.1007_s00362-022-01312-0
    DOI: 10.1007/s00362-022-01312-0
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    References listed on IDEAS

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    1. Jazaa S. Al-Mutairi & Mohammad Z. Raqab, 2020. "Confidence intervals for quantiles based on samples of random sizes," Statistical Papers, Springer, vol. 61(1), pages 261-277, February.
    2. M. S. Kotb & M. Z. Raqab, 2021. "Estimation of reliability for multi-component stress–strength model based on modified Weibull distribution," Statistical Papers, Springer, vol. 62(6), pages 2763-2797, December.
    3. El-Adll, Magdy E., 2011. "Predicting future lifetime based on random number of three parameters Weibull distribution," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(9), pages 1842-1854.
    4. Marco Burkschat & Erhard Cramer & Udo Kamps, 2003. "Dual generalized order statistics," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 13-26.
    5. Shah, Imtiyaz A. & Barakat, H.M. & Khan, A.H., 2020. "Characterizations through generalized and dual generalized order statistics, with an application to statistical prediction problem," Statistics & Probability Letters, Elsevier, vol. 163(C).
    6. Barakat, H.M. & El-Adll, Magdy E., 2009. "Asymptotic theory of extreme dual generalized order statistics," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1252-1259, May.
    7. Magdy E. El-Adll, 2021. "Inference for the two-parameter exponential distribution with generalized order statistics," Mathematical Population Studies, Taylor & Francis Journals, vol. 28(1), pages 1-23, January.
    8. Wang, Jianzhou & Qin, Shanshan & Jin, Shiqiang & Wu, Jie, 2015. "Estimation methods review and analysis of offshore extreme wind speeds and wind energy resources," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 26-42.
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